Subject tracking systems for a movable imaging system

ABSTRACT

A method for tracking a subject in successive image frames includes obtaining previous image frames with an imaging device, processing the previous image frames, obtaining motion information of the imaging device and a subject, determining a region of interest, obtaining a subsequent image frame, and processing the region of interest. The processing includes determining previous frame positions of the subject therein. The motion information is obtained with sensors physically associated with one or more of the imaging device and the subject. The region of interest is located in a predetermined spatial relationship relative to a predicted frame position of the subject.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims priority to and the benefit of U.S. ProvisionalApplication No. 62/364,960, filed Jul. 21, 2016, and U.S. ProvisionalApplication No. 62/372,549, filed Aug. 9, 2016, the entire disclosuresof which are incorporated by reference herein.

COPYRIGHT

A portion of the disclosure of this patent document contains materialthat is subject to copyright protection. The copyright owner has noobjection to the facsimile reproduction by anyone of the patent documentor the patent disclosure, as it appears in the Patent and TrademarkOffice patent files or records, but otherwise reserves all copyrightrights whatsoever.

TECHNICAL FIELD

The present disclosure relates to subject tracking systems for a movableimaging platform including enhancements to location prediction,trajectory generation, voice command recognition, compositionaltechnique, and system architecture and data-flow for tracking andsynchronization.

BACKGROUND

It is desirable in many circumstances to be able to track a particularsubject when recording video. Providing tracking commands to a movableimaging platform using manually operated controls may be too difficultand complex in certain situations, such as a situation where theoperator of the movable imaging platform is also a subject to betracked.

A tracking system works best when locations of the movable imagingplatform and subject can be accurately known. Global Positioning Systemreceivers can be utilized to provide a reasonable degree of accuracy,but they are not ideal in all circumstances.

It is also desirable in many circumstances to be able to track aparticular subject when recording video. Once a subject has beenidentified in a video stream by a subject tracking system, the trackingsystem may automatically or semi-automatically frame the subject withinthe video. Furthermore, it may be desirable to limit the region in whichan aerial-based subject tracking system operates in order ensure thesafety of the user and at the same time ensure that the tracking systemcontinues to function robustly.

SUMMARY

A movable imaging system may include a movable imaging assembly (MIA),such as an unmanned aerial vehicle (UAV), that has a movable imagingdevice, such as a camera, attached to it. The movable imaging system mayalso include a controller or external device that is communicativelyconnected to the MIA using, e.g., a wireless link.

According to an implementation, a method is provided for tracking asubject with an imaging system forming a part of a movable imagingassembly. The method incudes capturing an image frame using an imagingsensor of the imaging system and locating the subject within a region ofinterest in the image frame. The region of interest is determinedutilizing a motion model and data from a sensor associated with thesubject or the movable imaging assembly. The method can also includetransferring the image frame to an external device that is connected tothe MIA, displaying the transferred image frame on an external displayof the external device, and displaying a bounding box around the subjectin a position based on a position of the region of interest.

According to another implementation, a method is provided for tracking asubject with an imaging system forming a part of a movable imagingassembly. The method includes capturing a first image frame using animaging sensor of the imaging system and locating the subject within thefirst image frame at a first set of frame coordinates. The method thenincludes capturing a second image frame using the imaging sensor andlocating the subject within the second image frame at a second set offrame coordinates. The method further includes capturing a third imageframe using the imaging sensor, determining a third set of framecoordinates at which the subject is predicted to be using a motion modeland based on the first frame coordinates and the second framecoordinates, and defining a region of interest having a predefinedboundary based on the third set of frame coordinates. Finally, themethod includes locating the subject by searching within the region ofinterest.

According to another implementation, a method is provided for tracking asubject with an imaging system forming part of an MIA. The methodincludes specifying a constraint on movement that limits motion of theMIA relative to a frame of reference that is the target or a fixedglobal positioning satellite system frame and moving the MIA inaccordance with the specified constraints while capturing image frameswith an image sensor of the imaging system.

According to another implementation, a method is provided for tracking atarget with an imaging system forming part of an MIA. The methodincludes defining a movable first volume positioned relative to thetarget having a first boundary within which the MIA may allowably moveduring flight. The method then includes defining a movable second volumepositioned relative to the target and contained within the first volumehaving a second boundary within which the MIA may not allowably moveduring flight. The method further includes receiving, by the MIA, amovement command to a trajectory point within the second volume andmoving the MIA to a modified trajectory point within the first volumethat is not within the second volume and that is proximate to thetrajectory point. Finally, the method includes capturing an image withan image sensor of the imaging system while the MIA is at the modifiedtrajectory point.

According to another implementation, a method is provided for tracking atarget with an imaging system forming part of an MIA. The methodincludes selecting a compositional technique defining a composition toapply for image frames captured with an image sensor of the imagingsystem, detecting a movement of the target, calculating an MIAtrajectory point to achieve the composition for image frames predictedto be captured with the image sensor based on the movement of thetarget, moving the MIA to the calculated trajectory point, and capturingone or more image frames with the imaging system at the calculatedtrajectory point.

According to another implementation, a method is provided for tracking atarget with an imaging system forming part of an MIA that includesspecifying a constraint on movement that limits motion of the MIArelative to a frame of reference (FOR) that is the target or a fixedglobal positioning satellite system frame. The method also includesmoving the MIA in accordance with the specified constraints whilecapturing image frames with an image sensor of the imaging system. Inthe method, the specifying of the constraint on movement includesreceiving a voice command signal that is an audio signal or a digitalreproduction of the audio signal, performing a speech-to-text conversionon the received voice command signal to produce converted text,searching a command database containing valid commands using theconverted text to find a matching valid command that matches theconverted text, and determining the constraint on movement based on thematching valid command.

According to another implementation, a method is provided fordetermining a distance between an MIA and a moving target being trackedby an imaging device of the MIA, including analyzing signals ofultra-wide-band transceivers (UWBTs) distributed between the MIA and themoving target, each of the UWBTs being affixed to one of the MIA and themoving target, determining a distance between the MIA and the movingtarget based on the analyzed signals, and providing the determineddistance to a tracking system that is utilized by the MIA to track themoving target.

According to another implementation, a method is provided for tracking asubject with an imaging system forming part of an MIA. The methodincludes capturing a first image frame using an imaging sensor of theimaging system, transferring the first image frame to an external devicethat is connected to the MIA, locating the subject within thetransferred first image frame at a first set of frame coordinates,displaying the transferred first image frame on an external display ofthe external device, and displaying a bounding box around the subject inthe transferred first image frame on the external display. The methodfurther includes capturing a second image frame using the imagingsensor, transferring the second image frame to the external device,locating the subject within the transferred second image frame at asecond set of frame coordinates, displaying the transferred second imageframe on the external display, and displaying a bounding box around thesubject in the transferred second image frame on the external display.The method further includes capturing a third image frame using theimaging sensor, transferring the third image frame to the externaldevice, and determining a third set of frame coordinates at which thesubject is predicted to be using a motion model and based on the firstframe coordinates and the second frame coordinates. Finally, the methodfurther includes displaying a bounding box at a position related to thethird set of frame coordinates on the external display.

A method for tracking a subject in successive image frames includesobtaining previous image frames with an imaging device, processing theprevious image frames, obtaining motion information of the imagingdevice and a subject, determining a region of interest, obtaining asubsequent image frame, and processing the region of interest. Theprocessing includes determining previous frame positions of the subjecttherein. The motion information is obtained with sensors physicallyassociated with one or more of the imaging device and the subject. Theregion of interest is located in a predetermined spatial relationshiprelative to a predicted frame position of the subject.

A method for tracking a subject in successive image frames includesdetermining a predicted frame location of a subject, determining aregion of interest, obtaining a subsequent image frame, and processingthe region of interest to locate the subject. The predicted framelocation is a location at which the subject is estimated to appear in asubsequent image frame to be obtained at a subsequent time. Thedetermining of the region of interest includes determining the locationof the region of interest to be in a predetermined spatial relationshiprelative to the predicted frame location. The obtaining of thesubsequent image frame is performed at a subsequent time with an imagingdevice.

A movable imaging system includes a movable platform, an imaging device,and a tracking system. The movable platform is movable in real space.The imaging device is for capturing successive image frames that form avideo, and is connected to the movable platform. The tracking system isfor tracking a subject in the successive image frames. The trackingsystem locates a region of interest for a subsequent image frame at apredicted frame location of the subject in a future image frame. Thepredicted frame location is based on previous frame positions of thesubject in the successive images, motion information of the imagingdevice, and motion information of the subject. The tracking systemprocesses the region of interest of the future image frame to locate thesubject in the future image frame.

These and other objects, features, and characteristics of the systemand/or method disclosed herein, as well as the methods of operation andfunctions of the related elements of structure and the combination ofparts and economies of manufacture, will become more apparent uponconsideration of the following description and the appended claims withreference to the accompanying drawings, all of which form a part of thisspecification, wherein like reference numerals designate correspondingparts in the various figures. It is to be expressly understood, however,that the drawings are for the purpose of illustration and descriptiononly and are not intended as a definition of the limits of thedisclosure. As used in the specification and in the claims, the singularform of “a,” “an,” and “the” include plural referents unless the contextclearly dictates otherwise.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of a movable imaging system and high-levelcomponents according to various implementations of this disclosure.

FIG. 2A is a pictorial illustration of the MIA according to animplementation.

FIG. 2B is a pictorial illustration of the imaging device according toan implementation.

FIG. 2C is a pictorial illustration of an MIA controller and userinterface according to an implementation.

FIG. 2D is a pictorial illustration of the imaging device of FIG. 2Bwithin a movement mechanism.

FIG. 3 is a block diagram illustrating components of an imaging deviceaccording to an implementation.

FIG. 4A is a block diagram of a tracking system.

FIG. 4B is a is a flowchart of a technique for tracking a subject invideo image frames, which may be implemented by the tracking system ofFIG. 4A.

FIG. 5A is a flowchart of a technique for determining a region ofinterest, which may be used in the technique of FIG. 4.

FIGS. 5B-5C are pictorial representations of video image frames thatillustrate subject tracking with the technique of FIG. 5A.

FIG. 6A is a flowchart of another technique for determining a region ofinterest, which may be used in the technique of FIG. 4.

FIGS. 6B-6E are pictorial representations of video image frames thatillustrate subject tracking with the technique of FIG. 6A.

FIGS. 7A and 7B are pictorial illustrations of an imaging devicepositioned with respect to a target.

FIG. 7C is a pictorial perspective view of the MIA of FIG. 2A operatingwithin predefined volumes.

FIG. 8 is a pictorial representation of a video image frame thatillustrates an application of the rule of thirds.

FIG. 9 is a block diagram of an implementation of a voice recognitionsystem that may interact with a tracking system.

FIG. 10 is a pictorial diagram of a target T comprising a plurality ofselectable subjects.

FIG. 11 is a pictorial representation of an MIA, such as the MIA of FIG.2A, tracking a target using ultra-wide-band transceivers.

FIG. 12A is a block diagram of various modules of a combined imaging andtracking system, according to an implementation.

FIG. 12B is a block diagram of various modules of an un-optimizeddisplay system, according to an implementation.

FIG. 12C is a block diagram of various modules of an optimized displaysystem with a low-latency redundant detect and identify module,according to an implementation.

FIG. 12D is a block diagram of various modules of an optimized displaysystem using synchronization techniques, according to an implementation.

FIGS. 13-21 are block diagrams illustrating various architectureconfigurations for implementing certain functions of the movable imagingsystem.

All original Figures disclosed herein are © Copyright 2017 GoPro Inc.All rights reserved.

DETAILED DESCRIPTION

Implementations of the present technology will now be described indetail with reference to the drawings, which are provided asillustrative examples to enable those skilled in the art to practice thetechnology. The figures and examples below are not meant to limit thescope of the present disclosure to a single implementation orembodiment, but other implementations and embodiments are possible byway of interchange of or combination with some or all of the describedor illustrated elements. Wherever convenient, the same reference numberswill be used throughout the drawings to refer to same or like parts.

FIG. 1 is a block diagram of a movable imaging system 10 and high-levelcomponents according to various implementations of this disclosure. Themovable imaging system 10 may have two primary components: MIA 20 and anexternal device 50, such as an MIA controller with a user interface.These components may be communicatively connected via a link 55. Thelink 55 may be wireless or wired. Other components may also be includedwithin the movable imaging system 10. For example, the MIA 20 maycomprise an imaging device 100, such as a camera (as used herein, theterm “camera” is defined broadly to include any form of imaging device)that can be used to capture still and video images. The MIA 20 mayinclude a movable platform 40 that can be moved positionally and/orrotationally with respect to a fixed reference ground. The MIA 20 mayalso include an imaging device movement mechanism 30 that allows theimaging device 100 to move positionally and/or rotationally with respectto the movable platform 40.

In some implementations, the external device 50 may correspond to asmartphone, a tablet computer, a phablet, a smart watch, a portablecomputer, and/or another device configured to receive user input andcommunicate information with the imaging device 100, imaging devicemovement mechanism 30, and/or movable platform 40 individually, or withthe MIA 20 as a whole.

In one or more implementations, the link 55 may utilize any wirelessinterface configuration, e.g., WiFi, Bluetooth (BT), cellular data link,ZigBee, near field communications (NFC) link, e.g., using ISO/IEC 14443protocol, ANT+ link, and/or other wireless communications link. In someimplementations, the link 55 may be effectuated using a wired interface,e.g., HDMI, USB, digital video interface, display port interface (e.g.,digital display interface developed by the Video Electronics StandardsAssociation (VESA), Ethernet, Thunderbolt), and/or other interface.

The UI of the external device 50 may operate a software application(e.g., GoPro Studio®, GoPro App®, and/or other application) configuredto perform a variety of operations related to camera configuration,control of video acquisition, and/or display of video captured by theimaging device 100. An application (e.g., GoPro App)® may enable a userto create short video clips and share video clips to a cloud service(e.g., Instagram®, Facebook®, YouTube®, Dropbox®); perform full remotecontrol of imaging device 100 functions; live preview video beingcaptured for shot framing; mark key moments while recording (e.g.,HiLight Tag®, View HiLight Tags in GoPro Camera Roll®) for locationand/or playback of video highlights; wirelessly control camera software;and/or perform other functions. Various methodologies may be utilizedfor configuring the imaging device 100 and/or displaying the capturedinformation.

By way of an illustration, the UI of the external device 50 may receivea user setting characterizing image resolution (e.g., 3840 pixels by2160 pixels), frame rate (e.g., 60 frames per second (fps)), and/orother settings (e.g., location) related to an activity (e.g., mountainbiking) being captured by the user. The UI of the external device 50 maycommunicate these settings to the imaging device 100 via the link 55.

A user may utilize the UI of the external device 50 to view contentacquired by the imaging device 100. A display of the UI of the externaldevice 50 may act as a viewport into a 3D space of the content. In someimplementations, the UI of the external device 50 may communicateadditional information (e.g., metadata) to the imaging device 100. Byway of an illustration, the UI of the external device 50 may provideorientation of the UI of the external device 50 with respect to a givencoordinate system to the imaging device 100 to enable determination of aviewport location or dimensions for viewing of a portion of thepanoramic content, or both. By way of an illustration, a user may rotate(sweep) the UI of the external device 50 through an arc in space. The UIof the external device 50 may communicate display orientationinformation to the imaging device 100 using a communication interfacesuch as link 55. The imaging device 100 may provide an encoded bitstreamconfigured to enable viewing of a portion of the content correspondingto a portion of the environment of the display location as the imagingdevice 100 traverses the path. Accordingly, display orientationinformation sent from the UI of the external device 50 to the imagingdevice 100 allows user selectable viewing of captured image and/orvideo.

In many instances, it is desirable to track a target (which may includeone or more subjects) with the MIA 20. Various forms of tracking may beutilized, including those discussed below and in U.S. Provisional PatentApplication Ser. No. 62/364,960, filed Jul. 21, 2016, and hereinincorporated by reference in its entirety. A tracking system 60 may beutilized to implement the described forms of tracking. The trackingsystem 60 may comprise a processor and algorithms that are used fortracking the target. The tracking system 60 is shown in dashed linessince it may be included entirely within the MIA 20 or entirely withinthe external device 50, or portions of the tracking system 60 may belocated or duplicated within each of the MIA 20 and the external device50. A voice recognition system 70 may also be utilized to interact withthe tracking system 60. The voice recognition system 70 is defined inmore detail below.

FIGS. 2A-2D are pictorial illustrations of implementations of thecomponents shown in FIG. 1. FIG. 2A is a pictorial illustration of theMIA 20 according to an implementation. In the implementation shown, theMIA 20 includes a movable platform 40 that is a quadcopter drone, butthe invention is not limited to this implementation. The MIA 20 could beany form of an aerial vehicle or any form of movable device that ismovable with respect to a fixed ground, which could include movablemechanical systems that are tied to the earth. As shown in FIG. 2A, theimaging device 100 is fixedly mounted in the front of the movableplatform 40 so that it points in a direction along an axis of themovable platform 40. However, in various implementations, the mountingof the imaging device 100 to the movable platform 40 is done using theimaging device movement mechanism 30.

FIG. 2B is a pictorial illustration of the imaging device 100. In FIG.2B, the imaging device 100 is a GoPro Hero4® camera, however any type ofimaging device 100 may be utilized. The imaging device 100 may include avideo camera device. FIG. 2B also shows a lens 130 of the camera, alongwith a display screen 147.

FIG. 2C is a pictorial illustration of an external device 50,specifically, an MIA controller and user interface according to animplementation. The user interface may further comprise a display system51 with a display device 52. The MIA controller may further comprise acommunications interface via which it may receive commands both foroperation of the movable platform 40, such as the UAV or drone, andoperation of the imaging device 100. The commands can include movementcommands, configuration commands, and other types of operational controlcommands.

FIG. 2D is a pictorial illustration of the imaging device 100 within themovement mechanism 30. The movement mechanism 30 couples the imagingdevice 100 to the movable platform 40. The implementation of themovement mechanism 30 shown in FIG. 2D is a three-axis gimbal mechanismthat permits the imaging device 100 to be rotated about threeindependent axes. However, the movement mechanism 30 may include anytype of translational and/or rotational elements that permit rotationaland/or translational movement in one, two, or three dimensions.

As illustrated in FIG. 3, which is a block diagram illustratingcomponents of an imaging device 100 according to an implementation, theimaging device 100 may include a processor 132 which controls operationof the imaging device 100. In some implementations, the processor 132may include a system on a chip (SOC), microcontroller, microprocessor,CPU, DSP, ASIC, GPU, and/or other processors that control the operationand functionality of the imaging device 100. The processor 132 mayinterface with mechanical, electrical, sensory, or power modules and/ora UI module 146 via driver interfaces and/or software abstractionlayers. Additional processing and memory capacity may be used to supportthese processes. These components may be fully controlled by theprocessor 132. In some implementation, one or more components may beoperable by one or more other control processes (e.g., a GPS receivermay include a processing apparatus configured to provide position and/ormotion information to the processor 132 in accordance with a givenschedule (e.g., values of latitude, longitude, and elevation at 10 Hz)).

The imaging device 100 may also include image optics 134, which mayinclude the lens 130 as an optical element of the imaging device 100. Insome implementations, the lens 130 may be a fisheye lens that producesimages having a fisheye (or near-fisheye) field of view (FOV). Othertypes of image optics 134 may also be utilized, such as, by way ofnon-limiting example, one or more of a standard lens, macro lens, zoomlens, special-purpose lens, telephoto lens, prime lens, achromatic lens,apochromatic lens, process lens, wide-angle lens, ultra-wide-angle lens,fisheye lens, infrared lens, ultraviolet lens, perspective control lens,other lens, and/or other optical element. In some implementations, theoptics module 134 may implement focus controller functionalityconfigured to control the operation and configuration of the cameralens. The optics module 134 may receive light from an object and couplereceived light to an image sensor 136, discussed below.

The imaging device 100 may include one or more image sensors 136including, by way of non-limiting examples, one or more of acharge-coupled device (CCD) sensor, active pixel sensor (APS),complementary metal-oxide semiconductor (CMOS) sensor, N-typemetal-oxide-semiconductor (NMOS) sensor, and/or other image sensor. Theimage sensor 136 may be configured to capture light waves gathered bythe optics module 134 and to produce image(s) data based on controlsignals from a sensor controller 140, discussed below. The image sensor136 may be configured to generate a first output signal conveying firstvisual information regarding an object. The visual information mayinclude, by way of non-limiting example, one or more of an image, avideo, and/or other visual information. The optics module 134 and theimage sensor 136 may be embodied in a housing.

The imaging device may further include an electronic storage element 138in which configuration parameters, image data, code for functionalalgorithms and the like may be stored. In some implementations, theelectronic storage 138 may include a system memory module that isconfigured to store executable computer instructions that, when executedby the processor 132, perform various camera functionalities includingthose described herein. The electronic storage 138 may include storagememory configured to store content (e.g., metadata, images, audio)captured by the imaging device 100.

The electronic storage 138 may include non-transitory memory configuredto store configuration information and/or processing code configured toenable, e.g., video information and metadata capture, and/or to producea multimedia stream comprised of, e.g., a video track and metadata inaccordance with the methodologies of the present disclosure. In one ormore implementations, the processing configuration may include capturetype (video, still images), image resolution, frame rate, burst setting,white balance, recording configuration (e.g., loop mode), audio trackconfiguration, and/or other parameters that may be associated withaudio, video, and/or metadata capture. Additional memory may beavailable for other hardware/firmware/software needs of the imagingdevice 100. The memory and processing capacity may aid in management ofprocessing configuration (e.g., loading, replacement), operations duringa startup, and/or other operations. Consistent with the presentdisclosure, the various components of the imaging device 100 may beremotely disposed from one another and/or aggregated. For example, oneor more sensor components may be disposed distal from the imaging device100. Multiple mechanical, sensory, or electrical units may be controlledby a learning apparatus via network/radio connectivity.

The processor 132 may interface to the sensor controller 140 in order toobtain and process sensory information for, e.g., object detection, facetracking, stereo vision, and/or other tasks.

The processor 132 may also interface one or more metadata sources 144.The metadata sources 144, in more detail, may include sensors such as aninertial measurement unit (IMU) including one or more accelerometersand/or gyroscopes, a magnetometer, a compass, a global positioningsatellite (GPS) sensor, an altimeter, an ambient light sensor, atemperature sensor, a pressure sensor, a heart rate sensor, a depthsensor (such as radar, an infra-red-based depth sensor, such as aKinect-style depth sensor, and a stereo depth sensor) and/or othersensors. The imaging device 100 may contain one or more othermetadata/telemetry sources, e.g., image sensor parameters, batterymonitor, storage parameters, and/or other information related to cameraoperation and/or capture of content. The metadata sources 144 may obtaininformation related to environment of the imaging device 100 and aspectsin which the content is captured.

By way of a non-limiting example, the accelerometer may provide devicemotion information including acceleration vectors representative ofmotion of the imaging device 100, from which velocity vectors may bederived. The gyroscope may provide orientation information describingthe orientation of the imaging device 100, the GPS sensor may provideGPS coordinates, time, and identifying location of the imaging device100, and the altimeter may obtain the altitude of the imaging device100. In some implementations, the metadata sources 144 may be rigidlycoupled to the imaging device 100 such that any motion, orientation, orchange in location of the imaging device 100 also occurs for themetadata module 144.

The sensor controller 140 and/or the processor 132 may be operable tosynchronize various types of information received from the metadatasources 144. For example, timing information may be associated with thesensor data. Using the timing information, metadata information may berelated to content (photo/video) captured by the image sensor 136. Insome implementations, the metadata capture may be decoupled from thevideo/image capture. That is, metadata may be stored before, after, andin-between one or more video clips and/or images. In one or moreimplementations, the sensor controller 140 and/or the processor 132 mayperform operations on the received metadata to generate additionalmetadata information. For example, the processor 132 may integrate thereceived acceleration information to determine a velocity profile of theimaging device 100 during a recording of a video. In someimplementations, video information may consist of multiple frames ofpixels using any applicable encoding method (e.g., H.262, H.264,Cineform, and/or other codec). In some implementations, the imagingdevice 100 may include, without limitation, video, audio, capacitive,radio, vibrational, ultrasonic, infrared, radar, LIDAR and/or sonar,and/or other sensory devices.

The imaging device 100 may include audio devices 145, such as one ormore microphones configured to provide audio information that may beassociated with images acquired by the image sensor 136. Two or moremicrophones may be combined to form a microphone system that isdirectional. Such a directional microphone system can be used todetermine the direction or location of a sound source and/or toeliminate undesirable noise originating in a particular direction.Various audio filters may be applied as well. The sensor controller 140may receive image and/or video input from the image sensor 136 and audioinformation from the audio devices 145. In some implementations, audioinformation may be encoded using, e.g., AAC, AC3, MP3, linear PCM,MPEG-H, and/or other audio coding formats (audio codec). In one or moreimplementations of spherical video and/or audio, the audio codec mayinclude a 3-dimensional audio codec. For example, an Ambisonics codeccan produce full surround audio including a height dimension. Using aG-format Ambionics codec, a special decoder may not be required.

In some implementations, one or more external metadata devices (notshown) may interface to the imaging device 100 via a wired link (notshown), e.g., HDMI, USB, coaxial audio, and/or other interface. Themetadata obtained by the imaging device 100 may be incorporated into thecombined multimedia stream using any applicable known methodologies.

The imaging device 100 may include its own display (e.g., display 147shown in FIG. 2B) as a part of its UI 146. The display may be configuredto provide information related to camera operation mode (e.g., imageresolution, frame rate, capture mode, sensor mode, video mode, photomode), connection status (connected, wireless, wired connection), powermode (e.g., standby, sensor mode, video mode), information related tometadata sources (e.g., heart rate, GPS), and/or other information. TheUI 146 may include other components (e.g., one or more buttons)configured to enable the user to start, stop, pause, and/or resumesensor and/or content capture. User commands may be encoded using avariety of approaches, including but not limited to duration of buttonpress (pulse width modulation), number of button presses (pulse codemodulation), or a combination thereof. By way of an illustration, twoshort button presses may initiate sensor acquisition mode, and a singleshort button press may be used to communicate (i) initiation of video orphoto capture and cessation of video or photo capture (toggle mode) or(ii) video or photo capture for a given time duration or number offrames (burst capture). Other user command or communicationimplementations may also be realized, e.g., one or more short or longbutton presses.

In some implementations, the UI 146 may include virtually various typesof device capable of registering inputs from and/or communicatingoutputs to a user. These may include, without limitation, display,touch, proximity sensitive interface, light, sound receiving/emittingdevices, wired/wireless input devices and/or other devices. The UImodule 146 may include a display, one or more tactile elements (e.g.,buttons and/or virtual touch screen buttons), lights (LED), speaker,and/or other UI elements. The UI module 146 may be operable to receiveuser input and/or provide information to a user related to operation ofthe imaging device 100. The imaging device 100 may further include, insome implementations, an input/output (I/O) module 148. The I/O module148 may be configured to synchronize the imaging device 100 with othercameras and/or with other external devices, such as a remote control, asecond capture device, a smartphone, the UI of the external device 50 ofFIG. 1A, and/or a video server. The I/O module 148 may be configured tocommunicate information to/from various I/O components. In someimplementations the I/O module 148 may include a wired and/or wirelesscommunications interface (e.g., Wi-Fi, Bluetooth, USB, HDMI, WirelessUSB, Near Field Communication (NFC), Ethernet, a radio frequencytransceiver, and/or other interfaces) configured to communicate to oneor more external devices (e.g., UI of the external device 50 in FIG. 1and/or another metadata source). In some implementations, the I/O module148 may interface with LED lights, a display, a button, a microphone,speakers, and/or other I/O components. In one or more implementations,the I/O module 148 may interface to an energy source, e.g., a battery,and/or a DC electrical source.

In some implementations, the I/O module 148 of the imaging device 100may include one or more connections to external computerized devices toallow for, among other things, configuration and/or management of remotedevices, e.g., as described above with respect to FIG. 1 and/or asdescribed below with respect to FIG. 3. The I/O module 148 may includeany of the wireless or wireline interfaces discussed above, and further,may include customized or proprietary connections for specificapplications.

In some implementations, a communication device 150 may be coupled tothe I/O module 148 and may include a component (e.g., a dongle) havingan infrared sensor, a radio frequency transceiver and antenna, anultrasonic transducer, and/or other communications interfaces used tosend and receive wireless communication signals. In someimplementations, the communication device 150 may include a local (e.g.,Bluetooth, Wi-Fi) and/or broad range (e.g., cellular LTE) communicationsinterface configured to enable communications between the imaging device100 and a remote device (e.g., the UI of the external device 50 in FIG.1). The communication device 150 may employ communication technologiesincluding one or more of Ethernet, 802.11, worldwide interoperabilityfor microwave access (WiMAX), 3G, Long Term Evolution (LTE), digitalsubscriber line (DSL), asynchronous transfer mode (ATM), InfiniBand, PCIExpress Advanced Switching, and/or other communication technologies. Byway of non-limiting example, the communication device 150 may employnetworking protocols including one or more of multiprotocol labelswitching (MPLS), transmission control protocol/Internet protocol(TCP/IP), User Datagram Protocol (UDP), hypertext transport protocol(HTTP), simple mail transfer protocol (SMTP), file transfer protocol(FTP), and/or other networking protocols.

Information exchanged over the communication device 150 may berepresented using formats including one or more of hypertext markuplanguage (HTML), extensible markup language (XML), and/or other formats.One or more exchanges of information between the imaging device 100 andoutside devices may be encrypted using encryption technologies includingone or more of secure sockets layer (SSL), transport layer security(TLS), virtual private networks (VPNs), Internet Protocol security(IPsec), and/or other encryption technologies.

The imaging device 100 may include a power system 152 tailored to theneeds of the applications of the imaging device 100. For example, for asmall-sized, lower-power action camera having a wireless power solution(e.g. battery, solar cell, inductive (contactless) power source,rectification, and/or other power supply) may be used.

Location Prediction for Subject Tracking

Referring to FIGS. 4A-4B, a tracking system 300 and a method ortechnique 400 are provided tracking a subject S in successive imageframes obtained by the imaging device 100 (e.g., video). The trackingsystem 300 may be implemented wholly or partially by the tracking system60. It may be desirable in many circumstances to track a particularsubject when recording a video, such as by locating the subject insuccessive image frames of the video (e.g., identifying and determiningframe positions of the subject), for example, to control the imagingdevice 100 and/or MIA 20 to ensure that the subject S remains in theimage frames. Subject tracking may be difficult, for example, withsimultaneous movement of the subject and the imaging device 100 and/orby taking significant time and/or consuming significant computingresources when large amounts of video data are capture (e.g., highresolution image frames, such as 4k).

Rather than process (e.g., search) an entire image frame to locate(e.g., identify and/or determine a position of) the subject S therein,the technique 400 determines a region of interest (ROI) of the imageframe to be processed. The ROI is a portion (e.g., window) of the imageframe, which is smaller than the entire image frame and thereby requiresless time and/or less computing resources to be processed than theentire image frame.

As shown in FIG. 4A, the tracking system 300 includes various implementthe technique 400, and may also includes or be in communication withvarious sensors associated with the imaging device 100 and/or thesubject S. The tracking system 300 and its various modules areintroduced below at a high level with further description of thetechniques implemented thereby discussed in still further detail below.

The modules may be included in and/or operated by various components ofsystem 10 (e.g., the imaging device 20, the imaging device 100, theexternal device 50, the tracking system 60, etc.). For example, thetracking system 300 includes a module 310 (e.g., an ROI module) fordetermining the ROI for a particular image frame, a module 320 (e.g., animage capture module) for obtaining the imaging frame, and a module 330(e.g., an image processing module) for processing the image frame, suchas the ROI of the image frame. The tracking system 300 may also includea module 350 (e.g., a tracking control module) for controlling theimaging device 100 and/or the MIA 20.

The ROI module 310 include a module 312 for determining a visual motionestimate (e.g., a visual motion estimation module), a module 313 fordetermining an imaging device motion estimate (e.g., an imaging devicemotion estimation module, and/or a module 314 for determining a subjectmotion estimate (e.g., a subject motion estimation module), along with amodule 315 for determining a combined motion estimate (e.g., a combinedmotion estimation module), and a module 316 for determining the ROI(e.g., an ROI determination module). The ROI module 310 may furtherinclude a module 317 for determining relative motion between the subjectS and the imaging device (e.g., a relative motion estimation module).Various of the modules may be omitted in accordance with the technique400 and variations thereof described below.

The visual motion estimation module 312 may receive visual informationfrom the imaging processing module 330, such as previous positions ofthe subject S in previously captured image frames, from which the visualmotion estimate is determined.

The imaging device motion estimation module 313 may receive motioninformation of the imaging device 100, or other components of the MIA20, such as the movable platform 40 and/or the movement mechanism 30,with motion sensors 313 a physically associated therewith. The motionsensors 313 a associated with the imaging device 100 may include themetadata sources 144. The imaging device motion estimate is determinedfrom information received from the sensors 313 a, as discussed infurther detail below.

The subject device motion estimation module 314 may receive motioninformation of the subject S with motion sensors 314 a physicallyassociated therewith. For example, the motion sensors 314 a may besensors of the external device 50 being held or attached to the subjectS. The subject device motion estimate is determined from the informationreceived from the sensors 314 a.

The relative motion estimation module 317 may, if included, receivevisual information and/or motion information from the estimation modules312, 313, 314 and/or the sensors 313 a, 314 a.

The combined motion estimation module 315 receives the estimes from theestimation modules 312, 313, 314, 317 from which the combined motionestimate is determined.

The ROI determination module 316 receives the combined motion estimatefrom which the size and/or position of the ROI is determined.

As shown in the flowchart of FIG. 4B, the technique 400, which may beimplemented by the subject tracking system 300, generally includesoperations of determining 410 the ROI for an image frame IF_(t)corresponding to a time t, obtaining 420 the image frame IF_(t) at thetime t, and processing 430 the ROI of the image frame to locate asubject S within the image frame IF_(t), which may also includedetermining a size of the subject S in the image frame IF_(t). Thetechnique 400 may further include repeating 440 the determining 410, theobtaining 420, and the processing 430 for still further image framesIF_(t+1), IF_(t+2), . . . IF_(t+n) to be obtained at subsequent timest+1, t+2, . . . t+n. The technique 400 may also include controlling 450the imaging device 100 and/or the MIA 20 to track the subject S, forexample, to maintain the subject S in subsequent image frames. Forexample, the controlling 450 may include controlling the location and/ororientation of the movable platform 40 (e.g., using output devices, suchas a rotor), the location and/or orientation of the imaging device 100with respect to the movable platform 40 (e.g., by operating the movementmechanism 30), and/or by controlling the imaging device 100 (e.g., witha zoom function).

The image frame for which the ROI is determined may be referred to as asubsequent image frame or a future image frame. The determining 410 ofthe ROI may be performed in various manners described below, forexample, by the ROI module 310. The obtaining 420 of the image frame isperformed, for example, by the image capture module 320 with the imagingdevice 100, which may be part of the MIA 20, by capturing the imageframe as discussed above. The processing 430 of the ROI_(t) is performedfor the image frame IF_(t), for example, by the image processing module330 with the imaging device 100, the movable imaging assembly 20, theexternal device 50, and/or the tracking system 60 according to anysuitable technique to determine the frame position S_(POSt) in the imageframe IF_(t), such as by determining a centroid of the subject S.

The determining 410 of the ROI may be performed in various manners andmay include determining a position of the ROI for the image frame andmay further include determining a size of the ROI. For example, and asdiscussed in further detail below, ROI may be determined for a futureimage frame according to previous positions of the subject S withinpreviously obtained image frames, motion of the imaging device 100,motion of the subject S, relative motion between the imaging device 100and the subject S, or combinations thereof. Furthermore, the position ofthe ROI may be based on a position in which the subject S is predictedto be in the subsequent image frame. As used herein, the terms “frameposition” or “subject frame position” refer to the position of thesubject S in an image frame, which may include positions at which thesubject S has been determined to be located in obtained image frames andmay also include a position at which the subject S is located in anobtained image frame that has yet to be processed for locating thesubject S therein.

Referring to FIGS. 5A-5C, the ROI for a future image frame may belocated relative to the frame position of the subject S in a previousframe. FIG. 5A is a flowchart of a technique 510 for determining theROI, while FIGS. 5B-5C illustrate the technique 510 visually. Thetechnique 510 presumes close proximity of the subject S in successiveimage frames and does not predict or estimate specific future locationsat which the subject S might appear in a future image frames. Thetechnique 510 may, for example, be implemented by the ROI module 310,including the visual motion estimation module 312 and the ROIdetermination module 316.

The technique 510 may be used to perform the operation for thedetermining 410 of the ROI in the technique 400. The technique 510includes operations of obtaining 512 a first image frame IF_(t−1) at atime t−1 (See FIG. 5B), processing 514 a first image frame IF_(t−1) (oran ROI thereof) to determine a frame position S_(POSt−1) of the subjectS in the first frame IF_(t−1) (see FIG. 5B), and locating 516 theROI_(t) for a second image frame IF_(t) in a predetermined spatialrelationship relative to the first frame position S_(POSt−1) (see FIG.5C). The technique 510 may be repeated as part of the technique 400 forsubsequent image frames IF_(t+1), IF_(t+2), . . . , IF_(t+n). The firstimage frame IF_(t−1) may also be referred to as a prior or previousimage frame, while the second image frame IF_(t) may be referred to as asubsequent or future image frame or a successive image frame (e.g.,being obtained immediately subsequent to the first image frame IF_(t−1),for example, in a video stream obtained by the imaging device 100 at aframe rate, such as 30 fps).

The obtaining 512 of the first image frame IF_(t−1) may be the obtaining420 performed in the technique 400 for an image frame from prior to theimage frame IF_(t). The processing 514 may be for an entirety of theimage frame IF_(t−1), or may be for an ROI thereof (e.g., as determinedin a prior operation of the technique 510). The locating 516 of theROI_(t) may include centering the ROI_(t) on the frame positionS_(POSt−1) of the subject S in the first frame IF_(t−1). The ROI_(t)may, for example, be rectangular as shown (e.g., having a common aspectratio with the entire image frame), square, or another suitable shape.

The technique 510 may also include determining a size of the ROI_(t) Forexample, the size of the ROI_(t) may be determined according to a sizeof the subject S, for example, in the image frame IF_(t−1), for example,increasing or decreasing in size if the subject S appears in the imageframe IF_(t−1) larger or smaller as compared to a previous image frame.For example, the size of the ROI_(t) may be determined according to apredicted size of the subject S in the image frame IF_(t).Alternatively, the size of the ROI may be a default size or may be fixedas the technique 510 is performed for successive image frames. Generallyspeaking, a larger ROI_(t) results in a higher likelihood of the subjectS being within the image frame IF_(t), while a smaller ROI_(t) resultsin a lesser likelihood.

Referring to FIGS. 6A-6E a technique 610 and variations thereof areprovided for determining the ROI (i.e., the size and the location)relative to a predicted frame position of the subject S in the futureimage frame. Such techniques may be performed with various differentinformation and/or in various different manners. Such information mayinclude visual information obtained from previously obtained imageframes, motion information of the imaging device 100, and/or motion ofthe subject S, which may be obtained from the previously obtained imagesand/or various sensors associated therewith. The term “predicted frameposition” or “predicted subject frame position” refers to the positionat which the subject S is estimated (e.g., predicted, estimated, likely,etc.) to appear in the subsequent image frame. In some implementations,the technique 400 may include initially performing the technique 510 todetermine the ROI for one or more initial image frames (e.g., a secondimage frame in a video image stream), and include later performinganother technique (e.g., the technique 610) to determine the ROI forlater image frames (e.g., after sufficient visual and/or motion data isacquired to perform the technique 610). The technique 610 may beimplemented by the ROI module 310, including the visual, imaging device,subject, relative, and/or combined motions modules 312-315, 317 and theROI determination module 316.

FIG. 6A is a flowchart of a technique 610 for determining the ROI, whileFIGS. 6B-6E illustrate the technique 610 visually. The technique 610 maybe used to perform the operation for the determining 410 of the ROI_(t)in the technique 400. The technique 610 includes operations of:determining 620 a motion estimate of the subject S according topreviously obtained image frames (e.g., a visual motion estimate),determining 630 a motion estimate of the imaging device 100 in realspace (e.g., an imaging device motion estimate), and determining 640 amotion estimate of the subject S in real space (e.g., a subject motionestimate). The technique 612 further includes determining 650 a motionestimate of the subject S according to the one or more of the visualmotion estimate, imaging device motion estimate, and the subject motionestimate (e.g., a combined motion estimate), and determining 660 a sizeand location of the ROI_(t) from the combined motion estimate. The term“real space” refers to a fixed spatial frame of reference, which may beglobal coordinates or another defined coordinate system. The motionestimates may, for example, be estimates for a change of position of thesubject S in the image frames IF, or may be an estimate of motion of theimaging device 100 or the subject S from which estimates of the changesof position of the subject S may be derived.

The operation for the determining 620 of the visual motion estimate is,for example, performed by the visual motion estimation module 312according to a motion model. The visual motion estimate is an estimateof a change of position of the subject S in the image frame (e.g., achange in X, Y coordinates or predicted X, Y coordinates). The motionmodel uses the frame positions of the subject S in two or morepreviously obtained image frames IF_(t−m), . . . IF_(t−2), IF_(t−1) anda motion model to predict motion of the subject S, for example, from theimage frame IF_(t−1) to the image frame IF_(t). The determining 620generally includes operations of obtaining 622 the image framesIF_(t−m), . . . IF_(t−2), IF_(t−1) (see FIGS. 6B-6D), processing 624 theimage frames IF_(t−m), . . . IF_(t−2), IF_(t−1) to determine framepositions S_(t−m), . . . S_(t−2), S_(t−1) of the subject S therein (seeFIGS. 6B-6D), and determining 626 a visual motion estimate Δ_(x,y) ofthe subject S using the frame positions S_(t−m), . . . S_(t−2), S_(t−1)and a motion model (see FIG. 6E).

The motion model may, as illustrated in FIG. 6E, be a constant motionmodel that assumes constant motion of the subject S between the two mostrecent image frames (e.g., IF_(t−1) and IF_(t−2)) and between the mostrecent image frame and the subsequent image frame (e.g., IF_(t−1)). Forexample, the constant motion may be a two-dimensional frame positionchange Δ_(x,y), or may be a three-dimensional frame position changeΔ_(x,y,z) that additionally accounts for a distance in a directionperpendicular to the image frame (e.g., based on a change of size of thesubject S in the image frames or measured distances between the subjectS and the imaging device 100). Alternatively, the motion model may usemore than two frame positions from previously obtained image frames(e.g., three, four, or more), which may more accurately determine thevisual motion estimate by considering more information, for example,using line fitting (e.g., a linear motion model), curve fitting (e.g., acurvileinear motion model, for example, using polynomials and/orsplines), or a recursive filter (e.g., an extended Kalman filter (EKF)).

The determining 620 of the visual motion estimate may further includedetermining a confidence value associated therewith, which may bereferred to as a visual motion estimate confidence value. The confidencevalue is a measure of accuracy and/or certainty of visual motionestimate. The confidence value may be used in the determining 650 of thecombined motion estimate, for example, to weight and/or filter thevisual motion estimate among the imaging device motion estimate and thesubject motion estimate.

Instead or additionally, the visual motion estimate may be, or be basedon, relative motion of the imaging device 100 and the subject S asderived from the successive images. This may be referred to as arelative motion estimate, which may be determined by the relative motionestimation module 317. For example, direction and distance measurements(e.g., a vector) of the imaging device 100 and the subject S maycalculated from the frame positions of the subject S in previous imageframes and from a focal distance associated therewith (or other measureof distance between the subject S and the imaging device 100), andchanges therein. A motion model (e.g., line or curve fitting model) maybe applied to the previous direction and distance measurements topredict future relative motion of the imaging device 100 and the subjectS from which the visual motion estimate may be derived.

Instead or additionally, the visual motion may be based on motionvectors created during video processing (e.g., encoding and/orcompression techniques). When the image frames are encoded using certainvideo encoding techniques, such as H.264 (MPEG-4 Part 10, Advanced VideoCoding), the encoding utilizes motion vectors created by the videoencoder between the last and the current video image frames. Thesemotion vectors may be utilized to predict or refine the visual motionestimate.

The operation for the determining 630 of the imaging device motionestimate is, for example, performed by the subject motion estimationmodule 313 according to motion information of the imaging device 100.The imaging device motion estimate is an estimate of motion of theimaging device 100 in real space, for example, from time t−1 to t.Alternatively, the imaging device motion estimate may be an estimate ofmotion of the subject S between the image frame IF_(t−1) and the imageframe IF_(t) due to motion of the imaging device 100 in real space. Thedetermining 630 of the imaging device motion estimate generally includesoperations of obtaining 632 motion information of the imaging device100, and determining 634 the imaging device motion estimate from themotion information.

The motion information of the imaging device 100 may include orientationinformation and position information. The motion information may also bereferred to as egomotion. Orientation information may, for example,include roll, pitch, yaw, and higher order terms thereof, such asrotational velocity and/or rotational acceleration. Position informationmay, for example, include horizontal coordinates (e.g., globalpositioning or Euclidean coordinates), elevation, and higher order termsthereof, such as translational velocity and/or acceleration.

Orientation information and position information may be obtained fromthe various sensors 313 a physically associated with the imaging device100, such as the metadata sources 144. The various sensors may becoupled to the imaging device 100 itself, or may be coupled to othercomponents of the MIA 20, such as the movable platform 40 and theimaging device movement mechanism 30. In one example, the imaging device100 includes an embedded gyroscope, which includes one or moregyroscopes to detect rotation of the imaging device 100 in multiple axesrelative to real space (e.g., the roll, pitch, and yaw). In anotherexample, the MIA 20, or the movable platform 40 thereof, may include aglobal positioning system, a gyroscope, accelerometers, a barometer, acompass, an altimeter, a barometer, a magnetometer, an optical flowsensor, and/or an IMU (which may include one or more of theaforementioned sensors) from which the motion information (e.g.,orientation and/or position, or changes therein) of the movable platform40 may be determined in real space. The movement mechanism 30 mayadditionally include position sensors, which measure the motioninformation (e.g., orientation and/or position, or changes therein) ofthe imaging device 100 relative to the movable platform 40. Thus, frommotion information of the movable platform 40 and of the movementmechanism 30, motion information of the imaging device 100 may bedetermined.

Still further, motion information of the imaging device 100 in realspace may be obtained from the previously obtained image framesIF_(t−m), . . . , IF_(t−2), IF_(t−1). For example, the position and/ororientation of the imaging device 100 (e.g., the MIA 20) may be obtainedby observing changes in the frame position and/or size of referencespoints fixed in real space (e.g., features of the terrain which thesubject S may move relative to).

The determining 630 of the imaging device motion estimate may furtherinclude determining a confidence value associated therewith, which maybe referred to as an imaging device motion estimate confidence value.The confidence value is a measure of accuracy and/or certainty the ofimaging device motion estimate, which may, for example, be based on thereliability of the motion information (e.g., time delay and/or frequencyrelative to the time between successive image frames, accuracy of thesensors, availability and/or operation of the sensors, etc.). Theconfidence value may be used in the determining 650 of the combinedmotion estimate, for example, to weight and/or filter the subject motionestimate among the imaging device motion estimate and the subject motionestimate.

The operation for the determining 640 of the subject motion estimate is,for example, performed by the subject motion estimation module 314according to motion information of the subject S. The subject estimationis an estimate of motion of the subject S in real space and/or relativeto the imaging device 100, for example, from time t−1 to t.Alternatively, the subject motion estimate may be an estimate of motionof the subject S between the image frame IF_(t−1) and the image frameIF_(t) due to motion of the subject S in real space and/or relativemotion of the subject S to the imaging device 100. The determining 640of the subject motion estimate generally includes operations ofobtaining 642 motion information of the subject S, and determining 644the subject motion estimate from the motion information of the subjectS.

The motion information of the subject S may include positioninformation. The position information may, for example, includecoordinates (e.g., global positioning or Euclidean coordinates) and/orelevation of the subject S in real space, and higher order termsthereof, such as translational velocity and/or acceleration. Theposition information may instead or additionally include relativepositional information between the subject S and the imaging device 100,such as a distance therebetween and/or directional information (e.g., avector).

Position information may be obtained from various sensors 314 a and/ortransmitters physically associated with the subject S. For example, abeacon device, such as the external device 50, a smartphone,accelerometers, a dedicated beacon device, or the beacon schemadescribed below, may be carried by, coupled to, or otherwise physicallyassociated with the subject S. The sensors and/or transmitters may beused to determine the position, velocity, and/or acceleration of thesubject S in real space (e.g., as with a global positioning systemand/or accelerometers).

The determining 640 of the subject motion estimate may further includedetermining a confidence value associated therewith, which may bereferred to as subject motion estimate confidence value. The confidencevalue is a measure of accuracy and/or certainty of the subject motionestimate, which may, for example, be based on the reliability of themotion information (e.g., time delay and/or frequency relative to thetime between successive image frames, accuracy of the sensors, etc.).The confidence value may be used in the determining 650 of the combinedmotion estimate, for example, to weight and/or filter the subject motionestimate among the imaging device motion estimate and the subject motionestimate.

Instead or additionally, the subject motion estimate may be a measure ofrelative movement between the subject S and the imaging device 100. Thismay also be referred to as a relative motion estimate, which may bedetermined by the relative motion estimation module 317. For example,the imaging device 100, the MIA 20, and/or the subject S may includesensors 313 a, 314 a by which distance and direction may be measured.For example, the imaging device 100 and/or the MIA 20 may includesensors (e.g., ultrasonic transceivers) that send and receive signals bywhich a distance and changes in distance (e.g., direction) may bemeasured between the imaging device 100 and the subject S. Similarly,the subject S may include a transmitter (e.g., beacon) that sendssignals by which a distance and changes in distance (e.g., direction)may be measured (e.g., based on the time between sending and receivingthe signal).

The operation for the determining 650 of the combined motion estimateis, for example, performed by the combined motion estimation module 315according to the visual frame motion estimate, the imaging device motionestimate, and/or the subject motion estimate. The combined motionestimate is an estimate of the movement that the subject S will undergofrom the image frame IF_(t−1) to the future image frame IF_(t), or maybe the predicted frame position SPRED of the subject S in the imageframe IF_(t). The visual frame estimation, the imaging device motionestimate, and/or the subject motion estimate are combined (e.g., fused)to determine the combined motion estimate. As referenced above,confidence values associated with each of the visual frame motionestimate, the imaging device motion estimate, and the subject motionestimate may be used, for example, to weight and/or filter each suchestimation in determining the combined motion estimate. For example, theimaging device motion estimate, the subject motion estimate, and/or therelative motion estimate may be used to account for motion of theimaging device and the subject S (e.g., egomotion) by accounted for inthe visual motion estimate. For example, the imaging device motionestimate, the subject motion estimate, and/or the relative motionestimate may be determined as expected frame motion (i.e., a change ofposition of the subject S in the image frame) and be added (e.g., inweighted or unweighted form) to the visual motion estimate. By combiningthe various motion estimates, the ROI_(t) the predicted frame locationSPRED may be more accurate, thereby allowing the ROI_(t) to be sizedsmaller to provide reduced computing time and/or reduced computingresources for tracking the subject S in successive image frames.

The operation for the determining 660 of the size and the location ofthe ROI_(t) is, for example, performed by the ROI determination module316 and includes determining a predicted frame location SPRED of thesubject S in the image frame IF_(t) and locating the ROI_(t) relative tothe predicted frame location SPRED (e.g., in a predetermined location,such as centered on thereon).

The determining 660 also includes determining the size of the ROI_(t),which may include increasing or decreasing a size of the ROI_(t) ascompared to a previous ROI_(t−1). The size of the ROI_(t) may beincreased, for example, if the combined motion estimate indicates theimaging device 100 will be closer to the subject S, which would beexpected to appear larger in the image frame IF_(t) and possibly requireprocessing a larger portion of the image frame IF_(t) to locate thesubject S therein. The size of the ROI_(t) may also be increased, forexample, in circumstances in which the predicted location SPRED may beless reliable, for example, with faster movements (e.g., relativelylarge change between the predicted frame position SPRED and the previousframe position S_(POSt-1)) and/or relatively low confidence values beingassociated with each of the visual frame motion estimate, imaging devicemotion estimate, and/or the subject motion estimate. Alternatively, theROI_(t) may sized to a default size or may not change in size fordifferent image frames IF (e.g., have a fixed size, such as ¼, ⅛, or1/16 of a total size of the image frames).

Variations of the techniques 400, 510, and 610 are contemplated. Forexample, in the technique 610, the determining 650 of the combinedmotion estimate may be omitted, and the determining 660 of the ROI_(t)may be performed directly with the visual motion estimate, the imagingdevice motion estimate, and/or the subject motion estimate. Furthermore,one or more of the operations for the determining 626, 634, and 644 ofthe various motion estimates may be omitted with the operation for thedetermining 650 the combined motion estimate or the operation for thedetermining 660 of the ROI being performed with the image frames and/ormotion information from the operations of obtaining 622, 632, 642.

One or more of the modules 310-317, 320, 330 and the techniques 400,510, and 610 can be performed and/or implemented, for example, byexecuting a machine-readable program or other computer-executableinstructions, such as instructions or programs described according toJavaScript, C, or other such instructions. The steps, or operations, ofthe modules or techniques, or any other technique, method, process, oralgorithm described in connection with the implementations disclosedherein can be implemented directly in hardware, firmware, softwareexecuted by hardware, circuitry, or a combination thereof, for example,of the MIA 20, the imaging device 100, the external device 50, and/orthe tracking system 60.

Trajectory Generation for Subject Tracking

Degrees of Freedom

Once a subject or a target has been determined as present in a videostream as captured by an aerial subject tracking system or MIA 20, it isdesirable to automatically or semi-automatically accurately frame thesubject within the video image frames. For stationary targets, a manualframing may not be too difficult, once a manual control of the movableplatform 40 has been mastered. However, moving targets can present amuch more complex scenario, and a specific control becomes much moredifficult.

According to an implementation, an automatic or semi-automatic controlof the MIA 20 can be effected to operate within certain constraints.According to a first constraint, and referring to FIGS. 7A and 7B, whichare pictorial illustrations of the MIA 20 and the MIA's imaging device100 with respect to a target T, when the target T moves, a motion of theMIA 20 can be defined as having the MIA 20 follow the target T with aconstant delta in altitude (e.g., vertical) and horizontal position withrespect to the target T. A constant delta in the horizontal position canmean: a) the horizontal position of the target T is fixed within thevideo image frames, that is, the MIA 20 moves as the target T changesdirection of travel (e.g., the MIA 20 will remain behind the target, andadapt automatically to changes in direction of travel); or b) thehorizontal position of the target T is fixed in a GPS frame, meaning theMIA 20 position is fixed irrespective of a direction of travel of targetT. The motion of the MIA 20 may be described as relative to a frame ofreference (FOR) that is either a target T or a fixed GPS framework.

A user may provide input to the MIA 20 via an external device 50 such asthe MIA controller and UI described in respect to FIG. 1. This may allowcontrol of, or selection of, e.g., five DOFs, three of which are relatedto control of the movable platform 40 relative to the target, and two ofwhich are related to orientation of the imaging device 100 with respectto the movable platform 40.

As illustrated in FIG. 7A, according to an implementation, the MIA 20can be set to operate according to: a) a first DOF 740 in which the MIA20 moves in a radial direction towards or away from the target T; b) asecond DOF 741 in which the MIA 20 moves in a tangential direction,i.e., along a circular trajectory around target; and c) a third DOF 742in which the MIA 20 moves in a vertical direction or in altituderelative to the target T.

As illustrated in FIG. 7B, and according to an implementation, theimaging device 100 can be rotated by use of, e.g., the imaging devicemovement mechanism 30, such as a gimbal, to allow adjustment of theimaging device 100 within the MIA 20. The user input via the externaldevice 50 can thus be set to operate according to: d) a fourth DOF 743in which the horizontal position of the target T may be adjusted withinthe video stream by, e.g., pitching the imaging device movementmechanism 30; and e) a fifth DOF 744 in which the vertical position oftarget T within camera stream may be adjusted by yawing the imagingdevice movement mechanism 30 and/or the MIA 20.

By combining operations of all five DOFs 740, 742, 744, 746, 748discussed above, the MIA 20 and the imaging device 100 can automaticallyadjust position and orientation together with pitch and heading angle ofthe imaging device movement mechanism 30. This may ensure the correctplacement of the target T or subject within the image as well as thecorrect relative position of the MIA 20 with respect to the target T orsubject.

These DOFs 740, 742, 744, 746, 748 and constraints can be operatedindividually or in combination and may be choreographed over time toproduce complex motion of the imaging device 100 relative to the targetT. For example, for a first period of time, motion may be constrained tooperating solely within the second DOF 741, but then for a second periodof time, combined constraints of the first DOF 740, the third DOF 742,and fourth DOF 743 may be used in order to produce choreographedcinematic type video of the target T. The constraints may be implementedusing tracking techniques defined herein.

Flight Restriction Volumes

It may be desirable to create certain flight restriction volumes orzones in order ensure the safety of the user and at the same time ensurethat the tracking system associated with the MIA 20 continues tofunction robustly. To that end, regardless of other MIA 20 motiontrajectories or constraints, a further delineation of allowable andnon-allowable volumes relative to a target may be defined within whichflight is permitted or not permitted, respectively. These allowable andnon-allowable volumes may override other calculations of trajectoriesfor the MIA 20 in order to maintain safety of persons or property(including the MIA 20), or to ensure that the subject S remains withinview of the imaging device 100.

FIG. 7C is a pictorial perspective view of the MIA 20 operating withinpredefined volumes 745. A first volume 746 may be defined as anoutermost boundary within which the MIA 20 may operate. In oneimplementation, this first volume 746 could be, e.g., a half-sphere (orapproximation thereof) whose surface constitutes a predefined maximumallowable distance to the target T to ensure that the tracking systemdoes not lose the target T. This first volume 746 could also include aboundary that ensures that a distance between the MIA 20 and theexternal device 50 or the subject S (e.g., when using a GPS position ofthe subject), when a direct wireless link exists, does not exceed amaximum range of the wireless connection. The maximum range can bevariable and can be a function of the number of other devices operatingwithin a same Wi-Fi frequency spectrum or may be based on other factorsthat can impact transmission distances. A margin of safety may beapplied to any of the volumes, surfaces, or surface point distancesdiscussed herein. Other constraints may also be incorporated into thedefinition of the first volume 746, such as no-fly zones, etc.

A second volume 747 may be defined by, e.g., a cylinder, whose surfacerepresents a minimum distance to the target T and within whichconstitutes a no-fly zone around the subject to ensure the safety of thesubject. Finally, a third volume 748 may be defined that takes intoaccount a maximum extent of pitch permitted for the imaging device 100with respect to the MIA 20 in order to ensure that the tracking systemdoes not lose the target T. This third volume 748 may be defined as acone, and operation of the MIA 20 within this cone may be avoided.

These volumes 746, 747, 748 may also be designed to take intoconsideration motion of the target T in the image caused by the motionof the MIA 20. This motion may be kept within certain predefined limitsto ensure proper operation of the tracking system. In other words,changes in speed and direction of the MIA 20 may be constrained to occurbelow a certain change rate if the MIA 20 is operating in a mode whereit tracks the target T. If a motion estimate of the target T isavailable, this information may be incorporated to reduce the maximalallowed motion.

If a trajectory of the MIA 20 established by other criteria would causethe MIA 20 to enter a non-allowed volume, the trajectory may be modifiedso that it remains within an allowed volume. For example, the trajectoryof the MIA 20 may be modified to include a point within the allowedvolume nearest a point of the original trajectory that was within anon-allowed volume.

Scene Composition and Framing Preservation

Cinematography benefits significantly from utilizing composition andframing techniques that have been historically developed. Suchtechniques can be applied with regard to the images and video obtainedby use of the MIA 20. This introduces greater complexity than simplyidentifying and keeping track of a single subject or target T, as it mayinvolve cinematic framing and trajectory by defining, identifying,and/or detecting a subject, multiple subjects and/or a scene and/or acinematic element such as a backlight, horizon, or other compositionalaspects. The following techniques may be applied to the system.

First, consideration may be given to placement of a target T within aparticular scene. Determining which features form parts of the scene canbe useful so that the target T can be in front of the scene andpreferably not obscured by parts of the scene during movement. Backlightmay be considered to be in front of the scene and behind subject(s), andthe maintenance of backlight (or any other particular form of lighting)can be set as a parameter constraining motion. Fixtures or stationaryobjects may be considered as located in a fixed place throughout a scenewhereas subjects may be considered as dynamic actors within a scene.

FIG. 8 is a pictorial representation of a video image frame 630 d thatillustrates an application of the rule of thirds, which is splitting aframe into a three by three grid that defines ideal placement forvarious elements within the frame as shown. The imaging device 100 maybe positioned to maintain the horizon at an upper third position withinthe frame 630 d, here, along a topmost horizontal grid line, and thetarget T within the left third of the frame 630 d. In other applicationsof the rule of thirds, the horizon may be locked along the other of thehorizontal grid lines and the target T can be captured so as to belocated near various intersections of horizontal and vertical gridlines.

Other known compositional techniques may be further applied, such as thegolden ratio, use of diagonals, element balancing, leading lines,symmetry and patterns, and use of negative space, and/or othertechniques. A composition can ensure that there is adequate headroom forthe subject, i.e., that the subject is framed such that ratios betweensubject features, top of subject, and top of frame form a reasonableratio. Ratios may be sustained as the subject moves through the frameand as the imaging device 100 moves, for example, within or along withthe MIA 20. Furthermore, a composition can ensure that there is adequatelead room, i.e., adequate space in front of a subject's motion orsubject's heading.

All of the compositional techniques may be stored in a library alongwith algorithms and/or parameters used to define and implement thetechniques. One or more of these compositional techniques by beselectable and operable simultaneously.

Any of the techniques described above for determining motion of theimaging device 100 or predicting or restraining motion of the subject S(or the target T) may be applied to creating and maintaining thecompositional features described above. By way of example only, applyingthe constraints as described above with respect to FIGS. 7A and B may beutilized to create these specific compositional features.

Voice Command Tracking

When using visual tracking in a dynamic scenario (e.g., during actionsports), the operator of the MIA 20 may not have the time or may notwish to control the subject tracking via physical (e.g., “hands-on”)operation of the external device 50. This may occur in scenarios wherean operator of a tracking system 60 is also the target T that is beingtracked.

FIG. 9 is a block diagram of an implementation of a voice recognitionsystem 70 that may be utilized to perform the desired subject trackingwithout requiring, or by reducing, an amount of operator physicalinteraction with the external device 50. According to an implementation,the operator of the MIA 20 may carry or wear a microphone 710 connectedto a voice recognition unit 720 that interprets audio or voice commands725 from the operator and relays valid tracking commands 727 obtainedfrom a command database 730 to the tracking system 60 of FIG. 1. Thevoice recognition unit 720 may comprise a speech-to-text converter unit.A searching algorithm can locate commands associated with the convertedtext in the command database 730 containing valid commands.

Using the voice commands 750, the operator may direct the MIA 20 toexecute a wide variety of scripted flight maneuvers, which may bereferred to herein as “ProMoves,” and execute control over the MIA 20.Basic control commands, such as “startup,” “shutdown,” or “stop,” may beexecuted using the voice commands 750. ProMoves related to the variousforms discussed above may also be executed. In an example where thevoice command 750 includes “execute orbit at five meters altitude abovethe target T or a point of interest (POI) with a ten meter radius,” thetracking system 60 may instruct the MIA 20 to move to a height of fivemeters above the target T and then continuously move tangentially aboutthe target T at a distance of ten meters. The voice command 750 may alsoinstruct the MIA 20 to be positioned at an altitude five meters abovethe ground or to operate a “dronie” ProMove where the MIA 20 is directedto point at the target T or the POI and then fly backwards/upwards, etc.

A variety of measurement units may be utilized. For example, the unitsof feet and meters may be mixed together in a single command, and thevoice recognition unit 720 or the tracking system 60 could convert themixed units to a standardized set of units accordingly. Also, specificsas to a number of repeated operations could be received as part of thevoice command 750, such as “execute orbit twice.” In the eventinsufficient parameters are supplied to generate a complete command(e.g., the “ten meter radius” was omitted from the above voice command750), the operator could either be voice prompted for the additionalinformation and/or some predefined default value could be used.

Absolute distances may be used in the voice commands 750 (e.g., “executeorbit at five meters”) as well as relative distances (e.g., “executeorbit five meters higher”). In the event that a direction of travel orthe orientation of the subject is available, the operator may also givevoice commands 750 that take this information into account. For example,the voice command 750 can include language such as “take a shot from myright side”. The above voice commands 750 are presented as examples, butdo not constitute a comprehensive list of voice commands 750.

FIG. 10 is a pictorial diagram of a target T comprising a plurality ofselectable subjects S₁-S_(n) for use in describing implementationexamples for the voice recognition system 70 of FIG. 9. In addition tofocusing on a single subject S as a target T, the voice commands 750sent to the voice recognition system 70 may specify a collection ofsubjects S₁-S_(n) as the target T. The voice commands 750 may also beused to switch focus between several subjects S₁-S_(n).

The specifying of subject(s) S as targets T may be performed in at leasttwo ways: teaching and object recognition. In a first way (teaching),before a shot is taken, a teach-in phase is used where each subjectS₁-S_(n) is assigned a unique ID. Object recognition algorithms may beutilized to associate the subject S with its assigned ID. Then, in anoperational phase, the operator may switch the focus of the trackingsystem 60 during the shots to different subjects S₁-S_(n) using thevoice commands 750, such as “switch focus to subject S₁.” During theteach-in phase, instead of assigning unique IDs, actual names could beassigned to the subjects S₁-S_(n) to make operation simpler for theoperator (e.g., “switch focus to Alex”).

In a second way (object recognition), visual cues about objects may beused to select the subject(s) S₁-S_(n). Object attributes such as colormay be used (“switch focus to the person in the red shirt”). Objectattributes such as position (“switch focus to the object in the lowerleft-hand of the screen”) and shape may also be used, and these variousobject attributes may also be used in combination (“switch focus to theperson with long, straight, brown hair”).

In one example, the user may utilize the voice commands 750 within aplanned or scripted shot or scene that may be planned out in advanceusing, e.g., software planning tools, so that cues may be given to movethrough the shot. An example shot might be one that statically framestwo subjects S₁, S₂, then follows subject S₁ for ten seconds, thenfollows subject S₂ for five seconds, then pans out to frame bothsubjects S₁, S₂ with a horizon and other background elements of thescene. Such cinematic control could thus be integrated as part of thevoice recognition system 70, and the composition of the shot may becontrolled with commands such as: “places,” “action,” “next scene,”(another) “next scene,” “cut,” “take it from the top,” “take it from‘pan out.’” In this way, it is possible to create relativelysophisticated videos without requiring a high degree of physicalinteraction with the external device 50.

The types of control discussed above may be applied even when acontrollable UAV is not used as part of the MIA 20. For example, whenthe imaging device 100 is connected to the imaging device movementmechanism 30, such as the gimbal mechanism discussed above, but there isno movable platform 40 or it is not one that is remotely controllable(e.g., a downhill skier uses the imaging device 100 with the movementmechanism 30 mounted to the skier's helmet or handheld by the skier),various types of the voice commands 750, such as subject selection andthe like may still be utilized.

Ultra-Wide-Band Localization Using a Beacon Schema

A GPS device may be mounted to the MIA 20 and to the target T. Theabsolute positions of each may be read from the GPS devices and then arelative position between the two may be determined. However, theaccuracy of GPS devices, particularly in measuring altitude, isgenerally limited and not sufficient to allow precise subject trackingcontrol. It is desirable, when performing aerial subject tracking, toaccurately know the position of the target T with respect to the MIA 20.The use of GPS beacons, i.e., devices that use GPS satellites todetermine position and then broadcast that position to other GPSbeacons, may be applied in the context of aerial subject tracking.

FIG. 11 is a pictorial representation of an implementation of the MIA 20tracking a target T. In order to improve the accuracy in measuring adistance between the target T and the MIA 20, the system illustrated inFIG. 11 may utilize a set of ultra-wide-band transceivers (UWBTs) 800a-800 d (collectively or representatively, 800) to directly estimate arelative position and velocity of the target T with respect to the MIA20. This may be done by distributing UWBTs between the MIA 20 and themoving target T, for example, by affixing three or more UWBTs 800 a-800c with a known position (with respect to the MIA 20) on the MIA 20.Additionally, in this implementation, the target T has one additionalUWBT 800 d affixed to it.

This implementation presents a low-cost approach to create a localrelative position measurement system that can determine a distancebetween the MIA 20 and the movable target T having considerableaccuracy. The accurately determined distance can then be provided to thetracking system 60. Rather than using the UWBTs 800 in static scenarioswhere a set of anchor UWBTs are distributed on the ground, the UWBTs 800are positioned such that all are movable with respect to a fixed-frame(e.g., earth-based) reference coordinate system. Thus, thisimplementation performs subject tracking without requiring the use ofstatic beacons. Static beacons may take time (and effort, in difficultenvironments) to place, set up, initialize, and/or configure, and theuse of the MIA 20 may be restricted to locations close to where thestatic beacons are placed. A device that determines and analyzespositions calculated from the UWBTs can be located on the MIA 20 or thetarget T.

To perform subject tracking in this implementation, a distance betweenthe UWBT 800 d on the target T and each of the UWBTs 800 a-800 canchored on the MIA 20 may be measured by a known time-of-arrivalapproach. Once the individual distances are known, a relative positionof the target T may be derived using, e.g., known sphere intersectiontechniques for four or more UWBTs 800 a-800 d serving as anchors orknown triangulation techniques (when only three UWBTs 800 a-800 c serveas anchors).

By employing phase shift approaches, a relative direction of the targetT with respect to the MIA 20 may be derived. This becomes more usefulonce a position estimate degrades due to conditioning issues (e.g., asmall anchor baseline relative to the subject-UAV distance). By fixingan inertial measurement unit on one or more of the UWBTs 800 a-800 c ofthe MIA 20 and/or the UWBT 800 d on the target T, relative positionestimates may be improved. In addition, relative velocity estimates maybe improved, both in terms of relative positions (between the target Tand the MIA 20) and absolute positions (with respect to an earthframework).

Improvements in relative position and velocity estimates may beadvantageous since the high-level output of the system may be noisyposition measurements and/or a relative range between beacons. By fusingthis output with gyroscope and accelerometer data in a sensor fusionframework, the system may be able to: a) increase frequency (internalmeasurement unit (IMU) data may be higher frequency than UWBmeasurements); b) reduce noise in position estimates; c) obtain accuratevelocity information (by fusion of position and acceleration (which is asecond derivative of position)); and d) reduce a delay in a positionestimate by synchronizing a time between IMU measurements (very lowlatency) and UWBT measurements such that any delay in providing the UWBTmeasurements may be eliminated.

System Architecture and Dataflow: Latency and Synchronization

As described with respect to FIG. 1, the MIA 20 may include the imagingdevice 100, such as a camera, which may be mounted to the movableplatform 40, such as a drone, via an imaging device movement mechanism30, such as a gimbal as described above. The movement mechanism 30 canalso provide for active stabilization of the imaging device 100, and/orthe captured images themselves can be stabilized using image shakecorrection techniques. The external device 50, such as the MIAcontroller and user interface discussed above, may be utilized forcontrolling the MIA 20.

FIG. 12A is a block diagram of various modules of a combined imaging andtracking system 100, 60 according to an implementation. In order toperform subject following, algorithms of the tracking system 60 such asa detect and/or identify module 670 may be run on the imaging device 100or the MIA 20. A video stream and a metadata stream comprising thesubject stream may be provided as outputs to the link 55.

The processor on the imaging device 100 may be less powerful, due tosize and power constraints, than the processor on the external device50. In cases where the processors on the imaging device 100 and theexternal device 50 have similar power levels, the processor on theimaging device 100 may be performing its primary task of image capture,leaving little processing power for other tasks, such as tracking. Thus,running the tracking system 60 on the imaging device 100 may berelatively slow, introducing additional delay between the video streamand the bounding box stream. In order to reduce the delay whendisplaying the video stream to the user (with the bounding boxes aroundthe subject or using other metadata) on the display device 52 of theexternal device 50, the tracking and/or detection algorithms may bererun on the external device 50 that is displaying the video stream tothe user, the external device 50 having a more powerful processor.

Since a framerate of a video stream from the imaging device 100 may behigher than a framerate of the tracking system output (due to the highCPU load of the tracking system 60), the output of the tracking system60 (which may be, e.g., the bounding box around the subject S, but caninclude any metadata associated with the video data) can be disjointedand have a stuttering look and feel to the user.

In order to smooth the appearance of motion of the bounding box, motioninterpolation techniques that are applied to the subject S or the targetT and the MIA 20 discussed above can also be applied to the motion ofthe bounding box associated with the tracking system 60. Thisinterpolation may be done by using a motion model based on a previouslocation of the bounding box. The motion model can be based on fitting acurve (polynomial, spline), a recursive filter (such as an EKF), or someother method, as described above.

Output from the tracking algorithm running on the imaging device 100 maybe sent to the MIA 20 to be used for the actual tracking of the subjectS or the target T. The video stream from the imaging device 100 maysimultaneously be sent to the external device 50, and this video streammay then be used for the display system 51 of the external device 50.This arrangement reduces a delay that may be introduced by running thetracking and/or detection algorithms on the imaging device 100.

FIGS. 12B-12D are block diagrams of various modules of display systems(51, 51′, 51″) of external devices 50 according to variousimplementations. FIG. 12B is a block diagram of various modules of anun-optimized display system 51, which is provided with a metadata streamthat is an input to a video module 51 a that performs the overlayfunction for the display device 52. A video stream is provided as aninput to a video decoder 51 b. In FIG. 12B, the tracking overlay isdisplayed asynchronously with the decoded video on the display device52.

FIG. 12C is a block diagram of various modules of an optimized displaysystem 51′ with a low-latency redundant detect and/or identify module670′ according to an implementation. In order to reduce latency for thedisplay device 52 to the user on the display system 51′ of the externaldevice 50, the video stream may be fed to an input of the redundantdetect and/or identify module 670′ on the external device 50, and thetracking efficiency and robustness may be improved by using the motionestimates of the MIA 20 and the estimated position and velocity of thetarget T as discussed above. In this implementation, the metadata streammay not be needed by the display system 51′ since the metadata isdetermined by the redundant detect and/or identify module 670′. Thebenefit of this is that there may be a lower latency due to the displaysystem 51′ having more processing power and potentially dedicated imageprocessing hardware that can execute the algorithm more quickly withoutrequiring propagation of the metadata.

FIG. 12D is a block diagram of various modules of an optimized displaysystem 51″ using synchronization techniques according to animplementation. The detection and identification functions may addadditional latency to the system, and the tracking overlay or otherdetection/identification metadata output may trail the video framesconstituting the video stream.

In this implementation, the frame ID for each image frame is tagged andsent by the imaging and tracking system 100, 600 in the metadata stream.The system may be pipelined by forwarding the video before the detectionalgorithm is run. In this optimized display system 51″, both the videostream and the metadata stream arrive at a video and metadata syncmodule of the display system 51″ that is able to use the frame ID tosynchronize the video metadata with the video frames. The result is thatthe display device 52 can present the video with its tracking overlay ina synchronized manner while minimizing latency. Use of pipelining canminimize the overall latency, and the synchronizing matches the video tothe overlay.

FIGS. 13-21 are block diagrams that illustrate several architecturesthat may be utilized to implement, detect, identify, and drawfunctionalities as implemented by different components of the movableimaging system 10.

FIG. 13 is a block diagram that illustrates an architecture according toan implementation showing the imaging device 100, movable platform 40,and the external device 50 along with the functionalities of detect,identify, track, draw, select, and synchronize.

FIG. 14 is a block diagram illustrating the detect and identifyfunctions, which may constitute an image processing block with a frameinput and a frame-relative subject stream which contains data related toone or more subjects within the video image frame.

FIG. 15 is a block diagram illustrating the track function, which mayuse the current attitude and position of the movable platform 40, asubject stream, and a desired subject stream to compute a desiredtrajectory setpoint.

FIG. 16 is a block diagram illustrating the synchronize function (e.g.,“sync”), which may be used to implement an elastic buffer to partiallyor fully align the subject and video stream, although this module maynot be necessary if a synchronous architecture is chosen or anasynchronous architecture is chosen with acceptable video and subjectlayer misalignment.

FIG. 17 is a block diagram illustrating the select function that mayutilize a user input which is a screen position and the subject streamto compute a desired subject. The purpose of this module is to be ableto permit a “touch to select” of a subject on the screen.

FIG. 18 is a block diagram illustrating a draw function that may use thedesired subject stream or all subjects and the subject stream to computean on-screen display (OSD) overlay layer to be drawn on top of the videostream. The purpose of this module is to visualize the detected andidentified subjects on the UI of the external device 50.

Various alternate solutions can be also provided. For example, FIG. 19is a block diagram illustrating a distributed solution. In thissolution, the detect and identify functions are implemented on theimaging device 100, the track function is implemented on the movableplatform 40, and the draw, select, and synchronize functions areimplemented on the external device 50.

FIG. 20 is a block diagram illustrating a camera-centric solution inwhich the sync and draw functions are implemented on the imaging device100 instead of the external device 50.

FIG. 21 is a block diagram illustrating a controller-centric solution inwhich all functionality other than tracking is implemented in theexternal device 50. In this design, the sync function is not requiredsince this solution is completely synchronous.

In a distributed solution design, the detect and identify modules areimplemented and optimized for the imaging device 100. Support may beadded to handle a subject stream. The subject stream may contain, e.g.,a subject ID, a subject location in the image in, e.g., pixelcoordinates, a bounding box around a subject in pixels, a distance to asubject (in an absolute distance or up to scale). The video pipeline maybe optimized for low latency and the low resolution video (LRV) streammay be optimized as input for the detect and identify modules. Ametadata muxer may be configured to handle a subject stream and to writethe subject stream to, e.g., a session mp4 text track. The muxer may beconfigured to write the subject stream out to a USB/MTP interface.

In the moving platform 40 of the distributed solution design, a USB/MTPinterface may be configured to handle a subject stream. A universalasynchronous receiver/transmitter (UART) or other interface may beconfigured to push the subject stream and desired subject to a flightcontroller subsystem. A drone command and control (C&C) interface may beconfigured to handle the desired subject stream. It is possible toimplement the sync module before the muxer block, but this design ischosen to implement the sync, if needed, either further up or downstreamto minimize the total latency in the system.

In a flight controller of the moving platform 40 for the distributedsolution design, the tracking system may be implemented using thesubject stream and the desired subject to compute the desiredtrajectory. A desired MIA 20 trajectory setpoint may be parameterizedby, e.g., position, velocity, acceleration, or attitude of the MIA 20.The UART or other interface may be configured to handle the subjectstream and the desired subject. A state machine may be configured toimplement a tracking state.

The external device 50 in the distributed solution design may beutilized to implement the select, draw, and identify functions as wellas any further required UI functions. Optionally, the sync function maybe implemented by the external device 50 in order to align the videostream with the subject stream. The native system may be configured toreceive the subject stream over the interface of the movable platform 40and pass it to an application layer. The external device 50 additionallymay send the desired subject to the movable platform 40, while anapplication on the external device 50 may be configured to handle thesubject stream and desired subject as well.

The following description is focused on the differences between thecamera-centric and distributed solutions. The processor associated withthe movable platform 40 and the flight controller implementations neednot change. The imaging device 100 in the camera-centric solution issimilar to that of the distributed solution with the addition of syncand draw modules being moved to a position before an HDMI or high speedimage/data interface.

The following description is focused on the differences between thecontrol-centric and distributed solutions. The processor associated withthe movable platform 40 and flight controller implementations need notchange. The imaging device 100 of the control-centric solution may havean added feature that extends the USB/MTP interface to receive a subjectstream and mux into the session mp4 text track. In this design, theexternal device 50 may have the detect and identify functionsimplemented natively, and the draw function may be implemented nativelyas well. The sync function is removed because the design is synchronous.

Where certain elements of these implementations may be partially orfully implemented using known components, only those portions of suchknown components that are necessary for an understanding of the presentdisclosure have been described, and detailed descriptions of otherportions of such known components have been omitted so as not to obscurethe disclosure.

In the present specification, an implementation showing a singularcomponent should not be considered limiting; rather, the disclosure isintended to encompass other implementations including a plurality of thesame component, and vice-versa, unless explicitly stated otherwiseherein.

Further, the present disclosure encompasses present and future knownequivalents to the components referred to herein by way of illustration.

As used herein, the term “bus” is meant generally to denote all types ofinterconnection or communication architecture that may be used tocommunicate data between two or more entities. The “bus” could beoptical, wireless, infrared or another type of communication medium. Theexact topology of the bus could be for example standard “bus,”hierarchical bus, network-on-chip, address-event-representation (AER)connection, or other type of communication topology used for accessing,e.g., different memories in a system.

As used herein, the terms “computer,” “computing device,” and“computerized device” include, but are not limited to, personalcomputers (PCs) and minicomputers, whether desktop, laptop, orotherwise, mainframe computers, workstations, servers, personal digitalassistants (PDAs), handheld computers, embedded computers, programmablelogic device, personal communicators, tablet computers, portablenavigation aids, J2ME equipped devices, cellular telephones, smartphones, personal integrated communication or entertainment devices, orliterally any other device capable of executing a set of instructions.

As used herein, the term “computer program” or “software” is meant toinclude any sequence or human or machine cognizable steps which performa function. Such program may be rendered in virtually any programminglanguage or environment including, for example, C/C++, C #, Fortran,COBOL, MATLAB™, PASCAL, Python, assembly language, markup languages(e.g., HTML, SGML, XML, VoXML), as well as object-oriented environmentssuch as the Common Object Request Broker Architecture (CORBA), Java™(including J2ME, Java Beans), Binary Runtime Environment (e.g., BREW).

As used herein, the terms “connection,” “link,” “transmission channel,”“delay line,” and “wireless” mean a causal link between any two or moreentities (whether physical or logical/virtual) which enables informationexchange between the entities.

As used herein, the terms “integrated circuit,” “chip,” and “IC” aremeant to refer to an electronic circuit manufactured by the patterneddiffusion of trace elements into the surface of a thin substrate ofsemiconductor material. By way of non-limiting example, integratedcircuits may include field programmable gate arrays (e.g., FPGAs), aprogrammable logic device (PLD), reconfigurable computer fabrics (RCFs),systems on a chip (SoC), application-specific integrated circuits(ASICs), and/or other types of integrated circuits.

As used herein, the term “memory” includes any type of integratedcircuit or other storage device adapted for storing digital dataincluding, without limitation, ROM, PROM, EEPROM, DRAM, Mobile DRAM,SDRAM, DDR/2 SDRAM, EDO/FPMS, RLDRAM, SRAM, “flash” memory (e.g.,NAND/NOR), memristor memory, and PSRAM.

As used herein, the terms “microprocessor” and “digital processor” aremeant generally to include digital processing devices. By way ofnon-limiting example, digital processing devices may include one or moreof digital signal processors (DSPs), reduced instruction set computers(RISC), general-purpose (CISC) processors, microprocessors, gate arrays(e.g., field programmable gate arrays (FPGAs)), PLDs, reconfigurablecomputer fabrics (RCFs), array processors, secure microprocessors,application-specific integrated circuits (ASICs), and/or other digitalprocessing devices. Such digital processors may be contained on a singleunitary IC die, or distributed across multiple components.

As used herein, the term “network interface” refers to any signal, data,and/or software interface with a component, network, and/or process. Byway of non-limiting example, a network interface may include one or moreof FireWire (e.g., FW400, FW110, and/or other variation.), USB (e.g.,USB2), Ethernet (e.g., 10/100, 10/100/1000 (Gigabit Ethernet), 10-Gig-E,and/or other Ethernet implementations), MoCA, Coaxsys (e.g., TVnet™),radio frequency tuner (e.g., in-band or OOB, cable modem, and/or otherprotocol), Wi-Fi (802.11), WiMAX (802.16), PAN (e.g., 802.15), cellular(e.g., 3G, LTE/LTE-A/TD-LTE, GSM, and/or other cellular technology),IrDA families, and/or other network interfaces.

As used herein, the term “Wi-Fi” includes one or more of IEEE-Std.802.11, variants of IEEE-Std. 802.11, standards related to IEEE-Std.802.11 (e.g., 802.11 a/b/g/n/s/v), and/or other wireless standards.

As used herein, the term “wireless” means any wireless signal, data,communication, and/or other wireless interface. By way of non-limitingexample, a wireless interface may include one or more of Wi-Fi,Bluetooth, 3G (3GPP/3GPP2), HSDPA/HSUPA, TDMA, CDMA (e.g., IS-95A,WCDMA, and/or other wireless technology), FHSS, DSSS, GSM, PAN/802.15,WiMAX (802.16), 802.20, narrowband/FDMA, OFDM, PCS/DCS,LTE/LTE-A/TD-LTE, analog cellular, CDPD, satellite systems, millimeterwave or microwave systems, acoustic, infrared (i.e., IrDA), and/or otherwireless interfaces.

As used herein, the term “robot” may be used to describe an autonomousdevice, autonomous vehicle, computer, artificial intelligence (AI)agent, surveillance system or device, control system or device, and/orother computerized device capable of autonomous operation.

As used herein, the term “camera” may be used to refer to any imagingdevice or sensor configured to capture, record, and/or convey stilland/or video imagery which may be sensitive to visible parts of theelectromagnetic spectrum, invisible parts of the electromagneticspectrum (e.g., infrared, ultraviolet), and/or other energy (e.g.,pressure waves).

While certain aspects of the technology are described in terms of aspecific sequence of steps of a method, these descriptions are onlyillustrative of the broader methods of the disclosure and may bemodified as required by the particular application. Certain steps may berendered unnecessary or optional under certain circumstances.Additionally, certain steps or functionality may be added to thedisclosed implementations, or the order of performance of two or moresteps permuted. All such variations are considered to be encompassedwithin the disclosure.

While the above detailed description has shown, described, and pointedout novel features of the disclosure as applied to variousimplementations, it will be understood that various omissions,substitutions, and changes in the form and details of the devices orprocesses illustrated may be made by those skilled in the art withoutdeparting from the disclosure. The foregoing description is in no waymeant to be limiting, but rather should be taken as illustrative of thegeneral principles of the technologies.

What is claimed is:
 1. A method for tracking a subject in successiveimage frames comprising: obtaining previous image frames with an imagingdevice at previous times; processing the previous image frames todetermine previous frame positions of a subject therein; obtainingmotion information of the imaging device; obtaining motion informationof the subject from one or more sensors physically associated with thesubject; determining a region of interest for a subsequent image frameto be obtained at a subsequent time after the previous times, includingdetermining a predicted frame position of the subject in the subsequentimage frame from the motion information of the imaging device, themotion information of the subject, and the previous frame positions, andlocating the region of interest in a predetermined spatial relationshiprelative to the predicted frame position; obtaining the subsequent imageframe at the subsequent time; and processing the region of interest ofthe subsequent image frame to determine a frame position of the subject.2. The method of claim 1, wherein the determining the predicted frameposition is determined from the previous frame positions, motioninformation of the imaging device, and motion information of thesubject.
 3. The method of claim 1, further comprising determininganother region of interest for another subsequent image frame to beobtained at another subsequent time after the subsequent time, includingdetermining another predicted frame position of the subject in the othersubsequent image frame from at least one of the motion information or acombination of the subsequent frame position and one or more of theprevious frame positions; obtaining the other subsequent image frame atthe other subsequent time; and processing the other region of interestof the other subsequent image frame to determine another frame positionof the subject.
 4. A method for tracking a subject in successive imageframes comprising: determining a predicted frame location at which asubject is estimated to appear in a subsequent image frame to beobtained at a subsequent time; determining a region of interestcorresponding to the subsequent image frame, including determining alocation of the region of interest to be in a predetermined spatialrelationship relative to the predicted frame location; obtaining thesubsequent image frame at the subsequent time with an imaging device;and processing the region of interest of the subsequent image frame tolocate the subject, wherein the predicted frame location is determinedaccording to visual information from previous image frames, motioninformation of the imaging device, and motion information of thesubject, the motion information of the subject being obtained from oneor more sensors physically associated with the subject.
 5. The method ofclaim 4, wherein the predetermined spatial relationship is the predictedframe location centered in the region of interest.
 6. The method ofclaim 4, wherein the determining the region of interest includesdetermining a size of the region of interest.
 7. The method of claim 6,wherein the determining the size of the region of interest includesincreasing or decreasing the size of the region of interest relative toa previous region of interest corresponding to a previous image frame.8. The method of claim 6, wherein the size of the region of interest isdetermined according to at least one of a predicted size of the subjector a predicted distance between the subject and the imaging device inreal space.
 9. The method of claim 4, wherein the method furthercomprises obtaining the previous image frames with the imaging device,wherein the predicted frame location is determined according to thevisual information derived from the previous image frames, the previousimage frames were obtained by the imaging device, and the visualinformation includes previous frame positions of the subject within theprevious image frames.
 10. The method of claim 9, wherein predictedframe location is determined according to a visual motion estimate ofthe subject, the visual motion estimate being determined by applying amotion model to the previous frame positions.
 11. The method of claim 4,wherein the predicted frame location is determined according to themotion information of the imaging device obtained from one or moresensors physically associated with the imaging device.
 12. The method ofclaim 11, wherein the motion information of the imaging device includesone or more of position information and orientation information of theimaging device relative to real space.
 13. The method of claim 12,wherein predicted frame location is determined according to a imagingdevice motion estimate of the imaging device, and the one or moresensors include a gyroscope.
 14. The method of claim 4, wherein themotion information of the subject includes position information of thesubject relative to real space.
 15. The method of claim 14, wherein thepredicted frame location is determined according to a subject motionestimate of the subject.
 16. The method of claim 4, wherein thepredicted frame location is determined according to the image data fromthe previous image frames, the motion information of the imaging device,and the motion information of the subject.
 17. The method of claim 16,wherein the predicted frame location is determined according to a visualmotion estimate determined from frame positions of the subject in theprevious image frames, an imaging device motion estimate determined fromthe motion information of the imaging device obtained from a sensorphysically associated with the imaging device, and a subject motionestimate determined from the motion information of the subject obtainedfrom another sensor physically associated with the subject.
 18. Amovable imaging system comprising: a movable platform movable in realspace; an imaging device for capturing successive image frames that forma video and being connected to the movable platform; and a trackingsystem for maintaining a subject in the successive image frames, whereinthe tracking system locates a region of interest for a subsequent imageframe at a predicted frame location of the subject in a future imageframe based on previous frame positions of the subject in the successiveimages, motion information of the imaging device, and motion informationof the subject obtained from one or more sensors physically associatedwith the subject, and thereafter processes the region of interest of thefuture image frame to locate the subject in the future image frame.